ConfigProto

publiczna klasa końcowa ConfigProto

 Session configuration parameters.
 The system picks appropriate values for fields that are not set.
 

Protobuf typu tensorflow.ConfigProto

Klasy zagnieżdżone

klasa	ConfigProto.Builder		Session configuration parameters.
klasa	ConfigProto.Eksperymentalny		Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
interfejs	ConfigProto.ExperimentalOrBuilder

Stałe

wew	ALLOW_SOFT_PLACEMENT_FIELD_NUMBER
wew	CLUSTER_DEF_FIELD_NUMBER
wew	DEVICE_COUNT_FIELD_NUMBER
wew	DEVICE_FILTERS_FIELD_NUMBER
wew	EXPERIMENTAL_FIELD_NUMBER
wew	GPU_OPTIONS_FIELD_NUMBER
wew	GRAPH_OPTIONS_FIELD_NUMBER
wew	INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER
wew	INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER
wew	ISOLATE_SESSION_STATE_FIELD_NUMBER
wew	LOG_DEVICE_PLACEMENT_FIELD_NUMBER
wew	OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER
wew	PLACEMENT_PERIOD_FIELD_NUMBER
wew	RPC_OPTIONS_FIELD_NUMBER
wew	SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER
wew	SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER
wew	USE_PER_SESSION_THREADS_FIELD_NUMBER

Metody publiczne

wartość logiczna	zawieraDeviceCount (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wartość logiczna	równa się (obiekt obiektu)
wartość logiczna	getAllowSoftPlacement () Whether soft placement is allowed.
KlasterDef	pobierzClusterDef () Optional list of all workers to use in this session.
ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
statyczny plik ConfigProto	pobierz instancję domyślną ()
KonfiguracjaProto	getDefaultInstanceForType ()
końcowy statyczny com.google.protobuf.Descriptors.Descriptor	pobierzDescriptor ()
Mapa<String, Integer>	pobierz liczbę urządzeń () Zamiast tego użyj funkcji getDeviceCountMap() .
wew	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Mapa<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wew	getDeviceCountOrDefault (klucz ciągu, int wartość domyślna) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wew	getDeviceCountOrThrow (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Smyczkowy	getDeviceFilters (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ByteString	getDeviceFiltersBytes (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
wew	pobierz liczbę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ProtocolStringList	pobierz listę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Eksperymentalny	uzyskaj eksperymentalny () .tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
Opcje GPU	getGpuOptions () Options that apply to all GPUs.
Opcje GPULubBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
Opcje wykresu	getGraphOptions () Options that apply to all graphs.
GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
wew	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
wew	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
wartość logiczna	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
wartość logiczna	getLogDevicePlacement () Whether device placements should be logged.
długi	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
	getParserForType ()
wew	pobierzPlacementPeriod () Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
Opcje RPC	getRpcOptions () Options that apply when this session uses the distributed runtime.
RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
wew	getSerializedSize ()
ThreadPoolOpcjaProto	getSessionInterOpThreadPool (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
wew	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
Lista< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
Lista<? rozszerza ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
wartość logiczna	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
końcowy com.google.protobuf.UnknownFieldSet	getUnknownFields ()
wartość logiczna	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
wartość logiczna	maClusterDef () Optional list of all workers to use in this session.
wartość logiczna	maEksperymentalny () .tensorflow.ConfigProto.Experimental experimental = 16;
wartość logiczna	maGpuOpcje () Options that apply to all GPUs.
wartość logiczna	maGraphOptions () Options that apply to all graphs.
wartość logiczna	maRpcOptions () Options that apply when this session uses the distributed runtime.
wew	hashCode ()
końcowa wartość logiczna	jest zainicjowany ()
statyczny ConfigProto.Builder	nowyKonstruktor ()
statyczny ConfigProto.Builder	newBuilder (prototyp ConfigProto )
ConfigProto.Builder	nowyBuilderForType ()
statyczny plik ConfigProto	parseDelimitedFrom (wejście strumienia wejściowego)
statyczny plik ConfigProto	parseDelimitedFrom (dane wejścioweInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczny plik ConfigProto	parseFrom (dane ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczny plik ConfigProto	parseFrom (wejście com.google.protobuf.CodedInputStream)
statyczny plik ConfigProto	parseFrom (bajt [] dane, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)
statyczny plik ConfigProto	parseFrom (dane ByteBuffer)
statyczny plik ConfigProto	parseFrom (wejście com.google.protobuf.CodedInputStream, rejestr rozszerzenia com.google.protobuf.ExtensionRegistryLite)
statyczny plik ConfigProto	parseFrom (dane com.google.protobuf.ByteString)
statyczny plik ConfigProto	parseFrom (dane wejścioweInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczny plik ConfigProto	parseFrom (dane com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczny	parser ()
ConfigProto.Builder	do konstruktora ()
próżnia	writeTo (wyjście com.google.protobuf.CodedOutputStream)

Metody dziedziczone

Z klasy java.lang.Object

wartość logiczna	równa się (Obiekt arg0)
ostatnia klasa<?>	pobierzKlasę ()
wew	hashCode ()
ostateczna pustka	powiadomić ()
ostateczna pustka	powiadom wszystkich ()
Smyczkowy	doString ()
ostateczna pustka	czekaj (długi arg0, int arg1)
ostateczna pustka	czekaj (długi arg0)
ostateczna pustka	Czekać ()

Z interfejsu org.tensorflow.proto.framework.ConfigProtoOrBuilder

abstrakcyjna wartość logiczna	zawieraDeviceCount (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjna wartość logiczna	getAllowSoftPlacement () Whether soft placement is allowed.
abstrakcyjny ClusterDef	pobierzClusterDef () Optional list of all workers to use in this session.
abstrakcyjny ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
abstrakcyjna Mapa<String, Integer>	pobierz liczbę urządzeń () Zamiast tego użyj funkcji getDeviceCountMap() .
streszczenie wew	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjna Mapa<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
streszczenie wew	getDeviceCountOrDefault (klucz ciągu, int wartość domyślna) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
streszczenie wew	getDeviceCountOrThrow (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjny ciąg	getDeviceFilters (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie com.google.protobuf.ByteString	getDeviceFiltersBytes (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie wew	pobierz liczbę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
lista abstrakcyjna<String>	pobierz listę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie ConfigProto.Experimental	uzyskaj eksperymentalny () .tensorflow.ConfigProto.Experimental experimental = 16;
streszczenie ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
abstrakcyjne opcje GPU	getGpuOptions () Options that apply to all GPUs.
abstrakcyjne opcje GPUOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
abstrakcyjne opcje wykresu	getGraphOptions () Options that apply to all graphs.
streszczenie GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
streszczenie wew	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
streszczenie wew	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
abstrakcyjna wartość logiczna	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
abstrakcyjna wartość logiczna	getLogDevicePlacement () Whether device placements should be logged.
streszczenie długie	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
streszczenie wew	pobierzPlacementPeriod () Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
abstrakcyjne opcje RPCOptions	getRpcOptions () Options that apply when this session uses the distributed runtime.
streszczenie RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
streszczenie ThreadPoolOptionProto	getSessionInterOpThreadPool (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
streszczenie wew	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
lista abstrakcyjna< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
streszczenie ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
lista abstrakcyjna<? rozszerza ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
abstrakcyjna wartość logiczna	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
abstrakcyjna wartość logiczna	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
abstrakcyjna wartość logiczna	maClusterDef () Optional list of all workers to use in this session.
abstrakcyjna wartość logiczna	maEksperymentalny () .tensorflow.ConfigProto.Experimental experimental = 16;
abstrakcyjna wartość logiczna	maGpuOpcje () Options that apply to all GPUs.
abstrakcyjna wartość logiczna	maGraphOptions () Options that apply to all graphs.
abstrakcyjna wartość logiczna	maRpcOptions () Options that apply when this session uses the distributed runtime.

Stałe

publiczny statyczny końcowy int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER

Wartość stała: 7

publiczny statyczny końcowy int CLUSTER_DEF_FIELD_NUMBER

Wartość stała: 14

publiczny statyczny końcowy int DEVICE_COUNT_FIELD_NUMBER

Wartość stała: 1

publiczny statyczny końcowy int DEVICE_FILTERS_FIELD_NUMBER

Wartość stała: 4

publiczny statyczny końcowy int EXPERIMENTAL_FIELD_NUMBER

Wartość stała: 16

publiczny statyczny końcowy int GPU_OPTIONS_FIELD_NUMBER

Wartość stała: 6

publiczny statyczny końcowy int GRAPH_OPTIONS_FIELD_NUMBER

Wartość stała: 10

publiczny statyczny końcowy int INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER

Wartość stała: 5

publiczny statyczny końcowy int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER

Wartość stała: 2

publiczny statyczny końcowy int ISOLATE_SESSION_STATE_FIELD_NUMBER

Wartość stała: 15

publiczny statyczny końcowy int LOG_DEVICE_PLACEMENT_FIELD_NUMBER

Wartość stała: 8

publiczny statyczny końcowy w OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER

Wartość stała: 11

publiczny statyczny końcowy int PLACEMENT_PERIOD_FIELD_NUMBER

Wartość stała: 3

publiczny statyczny końcowy int RPC_OPTIONS_FIELD_NUMBER

Wartość stała: 13

publiczny statyczny końcowy int SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER

Wartość stała: 12

publiczny statyczny końcowy int SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER

Wartość stała: 17

publiczny statyczny końcowy int USE_PER_SESSION_THREADS_FIELD_NUMBER

Wartość stała: 9

Metody publiczne

publiczna wartość logiczna zawieraDeviceCount (klucz ciągu)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

publiczna wartość logiczna równa się (obiekt obiektu)

publiczna wartość logiczna getAllowSoftPlacement ()

 Whether soft placement is allowed. If allow_soft_placement is true,
 an op will be placed on CPU if
   1. there's no GPU implementation for the OP
 or
   2. no GPU devices are known or registered
 or
   3. need to co-locate with reftype input(s) which are from CPU.
 

bool allow_soft_placement = 7;

publiczny ClusterDef getClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public ClusterDefOrBuilder getClusterDefOrBuilder ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public static ConfigProto getDefaultInstance ()

publiczny ConfigProto getDefaultInstanceForType ()

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()

public Map<String, Integer> getDeviceCount ()

Zamiast tego użyj funkcji getDeviceCountMap() .

publiczny int getDeviceCountCount ()

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public Map<String, Integer> getDeviceCountMap ()

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public int getDeviceCountOrDefault (klucz ciągu, int wartość domyślna)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public int getDeviceCountOrThrow (klucz ciąg)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public String getDeviceFilters (indeks int)

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public com.google.protobuf.ByteString getDeviceFiltersBytes (indeks int)

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public int getDeviceFiltersCount ()

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public com.google.protobuf.ProtocolStringList getDeviceFiltersList ()

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

publiczne GPUOptions getGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

publiczne GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

public GraphOptions getGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

public GraphOptionsOrBuilder getGraphOptionsOrBuilder ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

public int getInterOpParallelismThreads ()

 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
 0 means the system picks an appropriate number.
 Negative means all operations are performed in caller's thread.
 Note that the first Session created in the process sets the
 number of threads for all future sessions unless use_per_session_threads is
 true or session_inter_op_thread_pool is configured.
 

int32 inter_op_parallelism_threads = 5;

public int getIntraOpParallelismThreads ()

 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
 0 means the system picks an appropriate number.
 If you create an ordinary session, e.g., from Python or C++,
 then there is exactly one intra op thread pool per process.
 The first session created determines the number of threads in this pool.
 All subsequent sessions reuse/share this one global pool.
 There are notable exceptions to the default behavior describe above:
 1. There is an environment variable  for overriding this thread pool,
    named TF_OVERRIDE_GLOBAL_THREADPOOL.
 2. When connecting to a server, such as a remote `tf.train.Server`
    instance, then this option will be ignored altogether.
 

int32 intra_op_parallelism_threads = 2;

publiczna wartość logiczna getIsolateSessionState ()

 If true, any resources such as Variables used in the session will not be
 shared with other sessions. However, when clusterspec propagation is
 enabled, this field is ignored and sessions are always isolated.
 

bool isolate_session_state = 15;

publiczna wartość logiczna getLogDevicePlacement ()

 Whether device placements should be logged.
 

bool log_device_placement = 8;

publiczny długi getOperationTimeoutInMs ()

 Global timeout for all blocking operations in this session.  If non-zero,
 and not overridden on a per-operation basis, this value will be used as the
 deadline for all blocking operations.
 

int64 operation_timeout_in_ms = 11;

publiczny getParserForType ()

public int getPlacementPeriod ()

 Assignment of Nodes to Devices is recomputed every placement_period
 steps until the system warms up (at which point the recomputation
 typically slows down automatically).
 

int32 placement_period = 3;

publiczne RPCOptions getRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

publiczne RPCOptionsOrBuilder getRpcOptionsOrBuilder ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

publiczny int getSerializedSize ()

public ThreadPoolOptionProto getSessionInterOpThreadPool (indeks int)

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

public int getSessionInterOpThreadPoolCount ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

lista publiczna< ThreadPoolOptionProto > getSessionInterOpThreadPoolList ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

publiczny ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder (indeks int)

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

lista publiczna<? rozszerza ThreadPoolOptionProtoOrBuilder > getSessionInterOpThreadPoolOrBuilderList ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

publiczna wartość logiczna getShareClusterDevicesInSession ()

 When true, WorkerSessions are created with device attributes from the
 full cluster.
 This is helpful when a worker wants to partition a graph
 (for example during a PartitionedCallOp).
 

bool share_cluster_devices_in_session = 17;

publiczny finał com.google.protobuf.UnknownFieldSet getUnknownFields ()

publiczna wartość logiczna getUsePerSessionThreads ()

 If true, use a new set of threads for this session rather than the global
 pool of threads. Only supported by direct sessions.
 If false, use the global threads created by the first session, or the
 per-session thread pools configured by session_inter_op_thread_pool.
 This option is deprecated. The same effect can be achieved by setting
 session_inter_op_thread_pool to have one element, whose num_threads equals
 inter_op_parallelism_threads.
 

bool use_per_session_threads = 9;

publiczna wartość logiczna hasClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

publiczna wartość logiczna maExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

publiczna wartość logiczna hasGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

publiczna wartość logiczna hasGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

publiczna wartość logiczna hasRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

publiczny int hashCode ()

publiczna końcowa wartość logiczna isInitialized ()

publiczny statyczny ConfigProto.Builder newBuilder ()

publiczny statyczny ConfigProto.Builder newBuilder (prototyp ConfigProto )

public ConfigProto.Builder newBuilderForType ()

public static ConfigProto parseDelimitedFrom (wejście strumienia wejściowego)

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public static ConfigProto parseDelimitedFrom (dane wejściowe wejściowe, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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public static ConfigProto parseFrom (dane ByteBuffer, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)

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Nieprawidłowy wyjątekProtocolBufferException

public static ConfigProto parseFrom (wejście com.google.protobuf.CodedInputStream)

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public static ConfigProto parseFrom (bajt [] dane, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)

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Nieprawidłowy wyjątekProtocolBufferException

public static ConfigProto parseFrom (dane ByteBuffer)

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Nieprawidłowy wyjątekProtocolBufferException

public static ConfigProto parseFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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public static ConfigProto parseFrom (dane com.google.protobuf.ByteString)

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public static ConfigProto parseFrom (dane wejściowe wejściowe, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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public static ConfigProto parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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publiczna statyka parser ()

public ConfigProto.Builder toBuilder ()

public void writeTo (wyjście com.google.protobuf.CodedOutputStream)

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